Paper on biomechnics

1. REVIEW ARTICLE
Biomechanics of human movement and its clinical
applications
Tung-Wu Lu*, Chu-Fen Chang
Institute of Biomedical Engineering, National Taiwan University, Taiwan
Received 7 July 2010; accepted 7 July 2010
Available online 9 January 2012
KEYWORDS
Biomechanics;
Computer modeling;
Human motion
analysis;
Imaging biomechanics
Abstract All life forms on earth, including humans, are constantly subjected to the universal
force of gravitation, and thus to forces from within and surrounding the body. Through the
study of the interaction of these forces and their effects, the form, function and motion of
our bodies can be examined and the resulting knowledge applied to promote quality of life.
Under gravity and other loads, and controlled by the nervous system, human movement is
achieved through a complex and highly coordinated mechanical interaction between bones,
muscles, ligaments and joints within the musculoskeletal system. Any injury to, or lesion in,
any of the individual elements of the musculoskeletal system will change the mechanical inter-
action and cause degradation, instability or disability of movement. On the other hand, proper
modification, manipulation and control of the mechanical environment can help prevent
injury, correct abnormality, and speed healing and rehabilitation. Therefore, understanding
the biomechanics and loading of each element during movement using motion analysis is help-
ful for studying disease etiology, making decisions about treatment, and evaluating treatment
effects. In this article, the history and methodology of human movement biomechanics, and
the theoretical and experimental methods developed for the study of human movement,
are reviewed. Examples of motion analysis of various patient groups, prostheses and orthoses,
and sports and exercises, are used to demonstrate the use of biomechanical and
stereophotogrammetry-based human motion analysis studies to address clinical issues. It is
suggested that further study of the biomechanics of human movement and its clinical applica-
tions will benefit from the integration of existing engineering techniques and the continuing
development of new technology.
Copyright ª 2011, Elsevier Taiwan LLC. All rights reserved.
* Corresponding author. Institute of Biomedical Engineering, National Taiwan University, Taiwan.
E-mail address: twlu@ntu.edu.tw (T.-W. Lu).
1607-551X/$36 Copyright ª 2011, Elsevier Taiwan LLC. All rights reserved.
doi:10.1016/j.kjms.2011.08.004
Available online at www.sciencedirect.com
journal homepage: http://www.kjms-online.com
Kaohsiung Journal of Medical Sciences (2012) 28, S13eS25

2. Introduction
All life forms on earth are subjected to gravity. How the
form, function and motion of these biological systems are
affected directly or indirectly by gravity has been a subject
of scientific study over centuries. It started with the
development of mechanics that were concerned with the
behavior of physical bodies when subjected to forces or
displacements, and the subsequent effect of the bodies on
their environment. More than 3000 years ago Babylonian
astronomers studied the problem of planetary positions.
The Renaissance astronomer Nicolaus Copernicus
(1473e1543) published his heliocentric theory in 1543,
which was in contrast to the widely accepted geocentric
system model popular during the 13th
e17th
centuries that
had been proposed by Aristotle (384e322 BC) and Claudius
Ptolemy (90ec.168). During the early modern period
(1453e1789), renowned scientists, including Galileo, Kep-
ler and Newton, laid the foundation of classical mechanics.
Galileo Galilei (1564e1642) worked theoretically and
experimentally on the motions of bodies, particularly of
falling bodies. Johannes Kepler (1571e1630) empirically
discovered his laws of planetary motion which gave an
approximate description of the motion of planets around
the sun and provided one of the foundations for Isaac
Newton’s theory of universal gravitation. In 1687 Isaac
Newton (1643e1727) used the newly developed mathe-
matics of calculus to give a detailed mathematical expla-
nation of mechanics and published his classic Philosophiae
Naturalis Principia Mathematica. In this three-volume
publication he formulated the law of universal gravitation
and the three laws of motion which can be applied to the
motion of planets in the heavens and all forms of move-
ments on earth [1,2]. Since all life forms on earth are under
the influence of universal gravitation, there is no doubt that
mechanics not only governs the motions of lifeless objects,
but also affects the form, motion and function of the bio-
logical systems on earth. The mechanical interactions within
the biological systems and with the environment received
attention from early scholars such as Aristotle, Leonardo da
Vinci (1452e1519), Galileo Galilei (1564e1642), Johannes
Kepler (1571e1630), Rene Descartes (1596e1650), and Isaac
Newton, among others, as well as from scientists of the
present day. Their efforts on the discovery of these
mechanical interactions have come to form a discipline of
research called biomechanics.
Biomechanics is the study of continuum mechanics (that
is, the study of loads, motion, stress, and strain of solids
and fluids) of biological systems and the mechanical effects
on the body’s movement, size, shape and structure.
Mechanical influence on biological systems can be found at
multiple levels, from molecular and cellular, all the way up
to the tissue, organ and system level. Therefore, the study
of biomechanics of humans ranges from the inner workings
of a cell, the mechanical properties of soft and hard
tissues, to the development and movement of the neuro-
musculoskeletal system of the body. Molecular biome-
chanics refers to the study of how mechanical forces and
deformation affect the conformation, binding/reaction,
function and transport of biomolecules, such as DNA, RNA
and proteins, and how mechanobiochemistry couples in
biomolecular motors and ion channel flows, etc. Cellular
biomechanics is concerned with the study of how cells
sense mechanical forces or deformations, and transduce
them into biological responses, especially for the study of
how mechanical forces alter cell growth, differentiation,
movement, signal transduction, protein secretion and
transport, gene expression and regulation. The properties
of living tissues are affected by applied loads and defor-
mations, and tissue biomechanics is mainly concerned with
the growth and remodeling of tissues as a response to
applied mechanical stimuli. For example, the effects of
elevated blood pressure on the mechanics of the arterial
wall, and the behavior of cardiomyocytes within a heart
with a cardiac infarct, have been widely regarded as
instances in which living tissue is remodeled as a direct
consequence of applied loads. Another example is Wolff’s
law of bone remodeling, developed by Julius Wolff
(1836e1902) in the 19th
century. Wolff’s laws states that
the internal architecture of the trabecular bone and the
external cortical bone in a healthy person or animal will
adapt to the loads placed on the bone and it will remodel
itself over time to become stronger to resist that type of
loading. The converse is also true. If the loading on a bone
decreases, the bone will become weaker owing to turnover
and a lack of stimulus for continued remodeling that is
required to maintain bone mass [2,3].
At the system level, mechanical factors also affect the
form, performance and function of the musculoskeletal
system. Human movement is achieved by a complex and
highly coordinated mechanical interaction between bones,
muscles, ligaments and joints within the musculoskeletal
system under the control of the nervous system [3]. Muscles
generate tensile forces and apply moments at joints with
short lever arms in order to provide static and dynamic
stability of the body under gravitational and other loads
while regularly performing precise limb control [3]. Any
injury or lesion of any of the individual elements of the
musculoskeletal system will change the mechanical inter-
action and cause degradation, instability or disability of
movement. On the other hand, proper modification,
manipulation and control of the mechanical environment
can help prevent injury, correct abnormality, and speed
healing and rehabilitation. Therefore, understanding the
biomechanics and loading of each element is helpful for
studying disease etiology, making treatment decisions and
evaluating the effects of treatment. However, because of
ethical considerations and technological limitations, direct
measurement of the forces transmitted in the human body is
possible only in exceptional circumstances, such as through
instrumented implants [4e7]. A further challenge is the
redundant nature of the musculoskeletal system. In the
human body there are more joints and muscles than are
necessary for performing our daily motor tasks. Therefore,
a certain task can be achieved by more than one musculo-
skeletal strategy. However, this compensatory mechanism is
essential for coping with the consequences of injuries or
diseases to the musculoskeletal system, but it makes it
difficult to determine the internal forces noninvasively.
Currently, combining noninvasive measurements of the
movement, such as the position of segments and the strain on
force-measuring instruments, with computer graphics-based
S14 T.-W. Lu, C.-F. Chang

3. anatomical modeling is a useful approach to estimating these
loadings. In this approach it is essential to integrate the
techniques of motion analysis and medical imaging. They
include measuring human motion and external loads,
developing three-dimensional (3D) computer graphics-based
biomechanical models based on medical imaging, calcu-
lating internal forces and validating the results. A validated
3D computer biomechanical model can then be applied to
the simulation of various movements and surgical proce-
dures. A recording of an electromyogram (EMG) of the active
muscles can further be used to understand the muscle
activity during human movement [8,9]. However, developing
a precise and noninvasive method for measuring the internal
force within the human body for clinical and other purposes
still remains a great challenge in the field of human biome-
chanics and motion analysis. In this article, a brief intro-
duction to the history and methodology of human movement
biomechanics is given, followed by a review of the theoret-
ical and experimental methods developed by the authors for
the study of human movement. The clinical applications of
these methods in various orthopedic and neurological
pathology contexts, and in sports medicine are also
described.
Human motion analysis
All movements and changes in movements arise from the
action of forces, both internal and external. A change in the
force acting on an object is necessary for moving an object
from a stationary position or for changing its velocity. The
amount of change in the velocity of an object depends on
the magnitude and direction of the applied force. Newton’s
laws of motion give a clear relationship between the
changing force and the resultant change in movement, and
this is applicable to all forms of movement, including
human locomotion [3]. Human motion analysis is the
systematic study of human motion by careful observation,
augmented by instrumentation for measuring body move-
ments, body mechanics and the activity of the muscles. It
aims to gather quantitative information about the
mechanics of the musculoskeletal system during the
execution of a motor task [10]. A special branch of human
motion analysis is gait analysis which is specific to the study
of human walking, and is used to assess, plan and treat
individuals with conditions affecting their ability to walk.
The following is a brief account of the history of human
motion analysis/gait analysis.
In pursuing mental and physical excellence, the ancient
Greeks found that harmony of mind and body required
athletic activity to complement the pursuit of knowledge.
Their interest in sport and human movement can be seen in
the predominance of kinematic representations of Greek
athletics in the artistic media. With the mechanical,
mathematical and anatomical paradigms developed during
Greek antiquity, the great philosopher Aristotle wrote the
first book on human movement (About the Movements of
Animals), which is the first scientific analysis of human and
animal movement in terms of observing and describing
muscular action and movement [2].
The great figure from the Renaissance, Leonardo da
Vinci, was the first to study human anatomy through
dissections of at least 30 cadaveric bodies. He was partic-
ularly interested in the structure of the human body as it
relates to performance, center of gravity, balance and
center of resistance. He identified muscles and nerves in
the human body and described the mechanics of the body
during standing, walking up- and downhill, rising from
a sitting position, jumping, and human gait. He also sug-
gested that cords be attached to a skeleton at the points of
origin and insertion of the muscles to demonstrate the
progressive action and interaction of various muscles during
movement [2].
Even though Leonardo da Vinci had produced very
detailed descriptions of the human body, it was not until
the mid-16th
century when Andreas Vesalius (1514e1564)
published the first anatomy book, De Humani Corporis
Fabrica (1543), which gave him the credit of being “The
Father of Modern Anatomy” [2]. Another two chief figures
of the Renaissance were Galileo Galilei and Giovani Alfonso
Borelli (1608e1679). While Galilei applied mechanical
theory to study animal movement, and published a treatise
De Animaliam Motibus (The movement of Animals) [2],
Borelli published De Motu Animalum (On the Motion of
Animals) in 1680 which successfully clarified muscular
movement and body dynamics. Borelli also estimated the
center of mass of the entire body by stretching the body out
on a rigid platform that was supported on a knife edge and
then repositioned until it was balanced [1]. Borelli is often
considered the “Father of Biomechanics” [2].
During the age of enlightenment (17th
e19th
centuries),
Wilhelm Eduard Weber (1804e1891) and his younger
brother, Eduard Friedrich Weber (1806e1871) published the
results of their collaborative study on the mechanism of
walking in mankind in 1836. Since then, the study of human
motion has greatly progressed from an observatory/
descriptive science to one based on quantitative measure-
ments, for which E´tienne-Jules Marey (1830e1904) made
the most important breakthrough. He determined a series
of actions of human locomotion in various forms according
to measurements of the effort exerted at each moment
using graphical methods, and glass-plate and celluloid film
chronophotography [1,2]. Carlet (1845e1892) added a heel
and separate forefoot chambers to Marey’s pressure-
recording shoes, obtaining more measurements of the
onset and duration of weight-bearing, and the vertical
reaction force [1].
Among the noted scientists, Eadweard Muybridge
(1830e1904) began what was probably the first assessment
of gait and deserves to be considered the “Father of Modern
Gait Analysis” [8]. Since Muybridge found that it was not
possible to capture the rapid limb movements of horses in
motion by eye [11], he improved photography by creating
a camera with a shutterspeed of up to 1/100 of a second and
recorded the motion in men, women, children, animals and
birds [1]. With the aid of computer vision and the techniques
of pattern recognition and artificial intelligence, photo-
grammetry using photographs, radiographs, and video
images continued to develop after Muybridge’s invention.
Stereophotogrammetry, the technique of measuring 3D
landmark coordinates, was then developed by the “Father of
Stereophotogrammetry”, Carl Pulfrich (1858e1929) [12].
Christian Wilhelm Braune (1831e1892) and Otto
Fischer (1861e1917) then used analytical close-range
Biomechanics of human movement S15

4. photogrammetry, combined with the geometrical properties
of central projection from multi-camera observations, to
estimate the 3D position data from digitized and noisy image
data [13]. In the 1890s, they used stereophotogrammetry
and ground reaction force (GRF) measurements to study the
biomechanics of human gait under loaded and unloaded
conditions using their pioneering 3D mathematical technique
based on Newtonian mechanics [14]. They also carefully
studied the mass, volume center of mass, and body segments
of three adult male cadavers and introduced the use of
regression equations for estimating body segment parame-
ters, based on the length and mass of body segments. To
date, the mathematical methodology of gait analysis
developed by Braune and Fischer has essentially remained
unchanged in modern gait analysis [1,2]. It is noted that
during the age of Enlightenment, computers had not yet
been developed. Therefore, manual involvement was
necessary for determining the specific markers on the human
body in each image, which was not only laborious and time-
consuming, but also one of the main sources of errors. This
inevitably limited the clinical application of the mainly two-
dimensional (2D) measurement and analysis of the human
motion during that period.
In the modern era (20th
century e today), human motion
analysis developed rapidly as the knowledge of anatomy
and mechanics, and measurement technology was
progressively established. In the 1940s, Harold Eugene
Edgerton (1903e1990) pioneered high-speed stroboscopic
photography that was used to photograph objects in motion
at a frequency of several million exposures per second.
During the 1970s, video camera systems, such as infrared
high-speed cameras, began their widespread application in
the analysis of pathological gait, producing detailed motion
analysis results within realistic cost and time constraints.
With the collocation of high-speed computers and video
camera systems, 3D analysis of human motion became
feasible. However, it had to wait until after World War II to
make its debut in clinical 3D applications.
After the war there were many retired soldiers who had
sustained limb injuries and who needed orthopedic treat-
ment, prostheses, orthoses and subsequent rehabilitation
for recovery of functional activities, especially for level
walking. In order to provide better medical services and
achieve treatment goals, numerous investigators devoted
themselves to the study of gait analysis for clinical appli-
cations. Among them was Verne Thompson Inman
(1905e1980) who began by applying the theory of mechan-
ical engineering to clinical problems, such as designing
prostheses for amputees. He studied the biomechanics of
locomotion and proved the assumption that the most effi-
cient gait pattern is achieved by minimizing vertical and
lateral excursions of the body’s center of gravity (COG). He
also identified the so-called gait determinants for normal
walking, i.e., features of the movement pattern that mini-
mizes these COG excursions [1]. He suggested that these
features be used to determine whether a movement pattern
is normal or pathological. Following Inman’s work, Jacquelin
Perry divided the gait cycle into five stance phase periods
and three swing phase periods [15]. David Sutherland refined
the definition of the gait cycle to have three periods of
stance, namely initial double support, single limb stance,
and second double support [16]. He also carried out
a comprehensive investigation on the walking patterns in
a total of nearly 300 normal children aged from 1 to 7 years
for the study of the development of mature gait [1,17].
Because of the tedious nature of processing and
analyzing cine film, the need for a more scientific approach
to automate the process led to the development of the 3D
Vicon motion capture system by Professor John P. Paul and
his PhD students, Mick Jarrett and Brian Andrews. This
system was made to capture human movement data in
numerical digits instead of analog data, and which is now
widely used in the study of human motion [1].
Apart from kinematic measurements using video
cameras, Dr J. Robert Close used a 16-mm movie camera with
a sound track for studying the phasic action of muscles in
subjects after muscle transfers for poliomyelitis. Doctor
Close was the first to record synchronously the kinesiological
electromyography (KEMG) of one muscle and kinematic data
on cine film [14]. Jacquelin Perry pioneered using fine wire
electrodes to record the gait electromyogram (EMG) and
used it as a primary clinical tool in determining the appro-
priateness of surgical procedures to correct gait deformities
[14]. Because muscles are the engines for producing active
movements, EMG has been a useful assessment tool for
detecting the electrical activity of specific muscles and
assessing their contribution to movement or gait. Between
1944 and 1947, Vern Inman and colleagues added KEMG to
other measurements, i.e., 3D force and energy, in the study
of walking in normal subjects and amputees, and thus
significantly moved the science of gait analysis forward.
The essential aim of human motion analysis is to
understand the mechanical function of the musculoskeletal
system during the execution of a motor task. Since the
forces for generating movement in the musculoskeletal
system are too difficult to measure noninvasively,
combined experimental and mathematical modeling
approaches have been used. The power of mathematical
modeling is that it enables the values of parameters which
are difficult or impossible to measure to be calculated from
the values of quantities which can be measured. An
example of this approach is determining the force in
a spring which cannot be measured directly. With the
measureable deformation of the spring, the force in the
spring can be calculated using Hooke’s law that relates the
deformation with the force in the spring (Fig. 1). Therefore,
Figure 1. Determining the nonmeasurable force (Df) in the
spring from the measured deformation of the spring (Dx) using
Hooke’s law.
S16 T.-W. Lu, C.-F. Chang

5. numerous studies have used mathematical modeling in
conjunction with noninvasive experimental measurements
to calculate nonmeasurable internal forces in the muscu-
loskeletal system through inverse dynamics analysis.
The measurable values of quantities in human motion
analysis are usually the motion of the musculoskeletal
system defined by skin markers and measured by the
motion capture systems, and the external forces applied to
this musculoskeletal system measured by force plates. With
the 3D trajectories of skin markers obtained using stereo-
photogrammetry, and the GRFs and center of pressure
(COP) measured using force plates, intersegmental forces
and internal moments at the joints of the lower limbs are
then calculated from the solution of equations based on
Newton’s laws of motion. This approach is called inverse
dynamics analysis.
Advances in techniques of human motion
analysis
Stereophotogrammetry-based human motion analysis has
been widely used in the diagnosis and subsequent planning
and evaluation of treatment of neuromusculoskeletal
pathology. However, there is still room for technological
improvement, including mathematical modeling of the
musculoskeletal system, quantitative validation of the
models for internal force estimation, and techniques to
quantify and minimize measurement errors, i.e., soft tissue
artifacts (STA). New technology for accurately determining
the skeletal motion of a joint is also needed to supplement
the measurement of the gross motion by the stereo-
photogrammetry systems.
One of the most successful applications of clinical gait
analysis is the surgical planning in cerebral palsy (CP)
[18,19]. A previous study of 70 CP patients showed that
after clinical gait analysis 89% of the original treatment
plans were altered and 39% of the recommended proce-
dures were not done [20]. However, this relies on extensive
team work in the interpretation of a huge bulk of data
derived from 3D motion analysis (Fig. 2), and which has
been a huge obstacle for applying gait analysis in a clinical
setting. Computer graphics-based models may be useful in
providing easy access to and visualization of gait analysis
results by creating a “look and feel” environment for the
user to examine the experimental data and interpret the
analytical results with relatively less effort. Traditionally,
the musculoskeletal system was modeled mathematically
as a multi-link system with individualized model parame-
ters, such as the length of each segment, the joint centre
positions, and the lines of action of the muscles and
tendons. The joints were often modeled as ball-and-socket
joints. This simplification made it difficult to describe the
precise motion of the joint, which directly affected the
accuracy of the lines of action and lever arms of the
surrounding muscles and tendons, and thus the estimated
internal forces. To address this problem, a mathematical
model of the human pelvis-leg system in the sagittal plane,
with an anatomical model of the knee, was developed to
calculate forces transmitted by the structural elements of
the system [21]. The sagittal plane model underestimates
the value of the maximum axial force in the femur during
walking by about 30% but suggests that 70% is due to the
action of the extensors or flexors. With advances in
computer graphics technology, a complete 3D computer
graphics-based geometrical model of the locomotor system
was developed with the anatomical structures recon-
structed from images produced by computed tomography
(CT) and magnetic resonance imaging (MRI) (Fig. 3) [9].
While information in the anatomical plane of interest is
helpful for clinical reference, a complete 3D data display
provides more realistic support for clinical decision-making
because the locomotor system itself and its responses to
the internal and external forces are 3D in nature. In addi-
tion, it would not be an easy task for clinicians to recon-
struct 3D knowledge of a complex movement by themselves
from individual components without any adequate tech-
nical support. In this regard, 3D solid modeling and image
Figure 2. Traditional gait output of (A) joint angles and (B) joint moments at the hip, knee and ankle of the right limb (black,
solid line) and left limb (black, dotted line) in a typical patient with spastic diplegia cerebral palsy and in that of the healthy
controls (gray, solid line) during level walking. BW: body weight; LL: leg length.
Biomechanics of human movement S17

6. display could be a good tool for presenting results and
surgical simulation.
Success of any theoretical model relies heavily on the
validation of its assumptions. The geometrical model of the
locomotor apparatus developed by the author was vali-
dated by EMG and telemetered force data from two
instrumented patients (Fig. 4) [22]. The model was used to
study the influence of activity of hip flexors and extensors
on the forces in the femur during isometric exercises and
during level walking. Kinematic and kinetic data, together
with simultaneous electromyography (EMG) and in vivo
axial forces transmitted along the prostheses from two
patients implanted with instrumented massive proximal
femoral prostheses, were obtained. A comparison of the
levels of the calculated axial forces in the femur model
agreed well with the simultaneous telemetered forces for
isometric tests [22]. Interaction between the muscles and
the bones during isometric tests was examined and biar-
ticular muscles were shown to play a major role in modu-
lating forces in bones. The study supports the hypothesis
that muscles balance the external limb moments, not only
at joints, but also along the limbs, decreasing the bending
moments but increasing the axial compressive forces in
bones. It is thus suggested that appropriate simulation of
muscle force is necessary in in vitro laboratory experiments
and in theoretical studies of load transmission in bones.
Knowledge of the forces and moments transmitted by the
bones is essential for the design and fixation of implants
and their preclinical testing. There is a similar need to
understand the effects of the mechanical environment on
fracture repair and limb lengthening procedures. Quanti-
tative validation of internal forces provided in this study is
of great help for the design of prostheses and related
rehabilitation applications.
Knowledge of accurate kinematics of natural human
joints, including 3D rigid body and surface kinematics, is
essential for the understanding of their function and for
many clinical applications. For this purpose, an accurate
measurement method for the kinematics of skeletal motion
is needed. Several techniques are available for measuring
3D joint kinematics, but few allow noninvasive measure-
ment with submillimeter accuracy. Imaging methods, such
as MRI and CT may be used to provide 3D geometry and
poses of bones, but they are limited to static and
nonweight-bearing conditions. Skin marker-based methods,
including stereophotogrammetry [23e33] and electromag-
netic tracking systems [34,35] have been widely used in
clinical settings for measuring the 3D kinematics of the
human body during functional activities. However, STAs are
Figure 3. Reconstruction of a 3D geometric computer model of (A) the pelvis and (B) the locomotor system from computed
tomography.
Figure 4. Instrumented massive proximal femoral prosthesis
that enables the measurement of femoral axial forces in vivo.
S18 T.-W. Lu, C.-F. Chang

7. difficult to prevent without the use of invasive bone pins
[36]. STAs are characterized by marker movement in rela-
tion to the underlying bone caused by skin deformation and
displacement, and have been regarded as the most critical
source of error in human movement analysis because of
their great influence on the estimation of skeletal system
kinematics [11,37,38]. In order to reduce the effects of
STA, several techniques in the literature have been used for
measuring 3D skeletal kinematics, including the use of
external fixators [39], intracortical pins [40] and percuta-
neous tracking devices [41], medical imaging methods
[42e44], as well as model-based registration methods
[45e47]. While the use of invasive approaches enables
direct measurement of the movement of bones and thus
the STA of the overlying skin markers, they affect the
motion of the subject and alter the soft tissue motion. The
risk of infection when applying these approaches is also of
great concern. Medical imaging methods, such as MRI [48]
and X-ray fluoroscopy [43,44], allow noninvasive measure-
ment of unrestricted joint motion in vivo but they are
limited to 2D or static measurements.
Surface model-based registration methods using
dynamic fluoroscopy systems have been proposed for the
accurate estimation of 3D poses (positions and orientations)
of knee prosthesis components [45,47,49e51]. All these
approaches work by registering the known 3D CAD surface
models of the prosthesis component to the dynamic fluo-
roscopic images. The surface model of a prosthesis
component is projected onto the fluoroscopic image plane,
and the pose of the component is then determined as the
3D pose of the component model that gives the best
correspondence between the fluoroscopic image and the
projected contours and/or areas of the model component.
These methods have been shown to have high accuracy
because the metallic components have precisely known
geometric features and produce sharp edges in fluoroscopic
images. The method has also been assumed to be appli-
cable to natural knee joints [48,52] but bones differ
fundamentally from total knee replacement (TKR) compo-
nents in their form and internal structure, resulting in
completely different fluoroscopic images. Bone edges are
less well-defined and it has been suggested that bone edge
attenuation is the primary factor limiting the theoretical
accuracy of this type of method [49]. Under real life
conditions, the accuracy would likely be worse. While
methods using bi-planar fluoroscopy [46,47] with better
accuracy than single-plane fluoroscopy have been
proposed, biplanar fluoroscopy methods inevitably increase
radiation doses and unacceptably constrain the motion of
the patient [53].
In order to bridge the gap in the in vivo measurement of
knee kinematics, the author and colleagues have developed
a volumetric model-based 2D to 3D registration method
with a new similarity measure, called the weighted edge-
matching score (WEMS), for measuring natural knee kine-
matics with single-plane fluoroscopy [50]. The 3D poses of
the bones were obtained by registering their volumetric CT
models to the corresponding fluoroscopy images using
digitally reconstructed radiographs (DRR) (Fig. 5). At each
image frame, an optimization procedure was used to find
the pose of the bone using the DRR which best matched the
fluoroscopic image according to the WEMS similarity
measure (Fig. 6). The performance of this registration
method in the measurement of the knee poses was previ-
ously evaluated using a cadaveric knee [50]. The means and
standard deviations of the discrepancies between the
measurements and the gold standard were 0.24 Æ 0.77 mm,
0.41 Æ 3.06 mm and 0.59 Æ 1.13
for in-plane translation,
out-of-plane translation, and all rotations, respectively.
Since STA is critical in the measurement accuracy of skin
marker-based stereophotogrammetry, it is necessary to
quantify the STA during functional activities for establishing
guidelines for selecting marker locations and for developing
compensation methods in human motion analysis. Three-
dimensional movements of skin markers relative to the
underlying bones in normal subjects during functional
activities were measured for the first time in the literature
using a noninvasive method based on integrating 3D fluo-
roscopy (WEMS) and stereophotogrammetry [54]. Gener-
ally, thigh markers had greater STA than shank markers,
and the STA of markers close to the knee joint were greater
than those away from the joint. The STA of the markers
showed nonlinear relationships with knee flexion angles and
some of their patterns were different between activities.
The STA of a marker also appeared to vary among subjects
and was affected by more than one joint. These results
suggest that correction of STA of individual markers during
a functional activity using a linear error model based on STA
measured from static isolated joint positions may not
produce satisfactory results. In addition to improving the
experimental measurements by judiciously determining
marker placement, compensation of STA in human motion
analysis may have to consider the multi-joint nature of
functional activities by using a global compensation
approach with individual anthropometric data [54].
Techniques in the literature for reducing the effects of
STA can be divided up into those which model the skin
surface and those which include joint motion constraints
[37]. Traditional segment-based methods treat each body
segment separately without imposing joint constraints,
resulting in apparent dislocations at joints predominantly
because of STA. Including joint constraints in a global STA
minimization approach, called a global optimization
method (GOM) [38], is regarded as an effective solution for
reducing the effects of STA on the skeletal system
Figure 5. Perspective projection model of the fluoroscopy
system. X- and Y-axes define the image plane. Rays of the point
source X-ray passing through the CT volume are projected onto
the image plane to form a DRR.
Biomechanics of human movement S19

8. kinematics [37]. The GOM, first proposed by the author and
colleagues, is based on minimizing the weighted sum of the
squared distances between measured and model-
determined marker positions with joint constraints for
simultaneously determining the spatial pose of all segments
of a multi-link model of the locomotor musculoskelatal
system [38]. Numerical experiments were used to show that
the GOM was capable of eliminating joint dislocations and
giving more accurate model position and orientation esti-
mates. It was suggested that, with joint constraints and
a global error compensation scheme, the effects of
measurement errors on the reconstruction of the muscu-
loskeletal system and subsequent mechanical analyses
could be reduced globally [37]. The GOM minimizes errors
not only in flexion/extension at joints, but also in axial
rotations and ab/adductions, and this improvement
contributes to extending the applicability of gait analysis to
clinical problems [37,38].
Applications of human motion analysis
With the development of theoretical and experimental
methods to improve accuracy and reliability, human motion
analysis has become a useful investigative and diagnostic
tool in many research and clinical areas, such as medicine,
ergonomics and sports, to name but a few. Through human
motion analysis, the deviations from normal movement in
terms of the altered kinematic, kinetic or EMG patterns can
be identified and then used to evaluate the neuro-
musculoskeletal conditions, to help with subsequent
treatment planning and/or to assess the efficacy of treat-
ment in various patient groups, such as those with CP
[18,19], stroke [55e61], knee osteoarthritis (OA) [62e69],
diabetes mellitus (DM) [70,71], and spinal cord injury (SCI)
[72]. Human motion analysis has also seen many applica-
tions in assistive technology, such as prosthetics and
orthotics, in which accurate evaluation of critical joint
motion characteristics can be obtained from human motion
measurements. In sports science and medicine, human
motion analysis is also widely used to help optimize athletic
performance and to identify mechanisms of common sports
injuries and the accompanied posture-related or
movement-related problems. A brief review of the spec-
trum of the applications of human motion analysis is given
below.
Evaluation of musculoskeletal pathology
and assessment of treatment efficacy
Pathological motion is a result of the response and/or
compensations of the neuromusculoskeletal system for the
underlying pathologies. Analysis of the deviations of motion
should thus permit an evaluation of the pathology to be
made, and should be helpful for subsequent planning and
assessment of treatment. Many leading orthopedic hospi-
tals worldwide now have gait laboratories which are
routinely used in a large number of cases, both to design
treatment plans, and for follow-up monitoring. Based on
gait analysis results, the development of treatment regimes
advanced significantly in the 1980s, including in orthopedic
surgery. For example, gait analysis has been used in
assisting with evaluating the pathological condition and
with surgical planning for children with CP. CP is charac-
terized by impaired motor control affecting movement and
posture with bony deformities and changes in the joint and
muscle properties. Common treatment options for the
paralysis of spastic muscles in patients with CP include
Botox injection or the lengthening, re-attachment or
detachment of particular tendons. Corrections of distorted
bony anatomy are also commonly undertaken in these
patients. It has been shown that motion analysis data can
alter recommendations for surgical intervention and ulti-
mately reduce the amount of surgery in children with CP
[20,73]. From 2005, in cooperation with the Pediatric
Division, Department of Orthopedic Surgery, National Tai-
wan University Hospital, clinical gait analysis services have
been offered for patients with neuromusculoskeletal
pathology at the Motion Analysis Laboratory at the Institute
of Biomedical Engineering, National Taiwan University. A
team of orthopedic surgeons, rehabilitation physicians,
Figure 6. A volumetric model-based 2D to 3D registration method with a new similarity measure, called the weighted edge-
matching score (WEMS), for measuring natural knee kinematics with single-plane fluoroscopy. (A) Lateral view and (B) oblique view.
S20 T.-W. Lu, C.-F. Chang

9. physical therapists, occupational therapists and biome-
chanical engineers work together to support the service.
Motion analysis techniques have been used to study the
effects of the severity of knee OA on the compensatory gait
patterns and whether these gait changes would help
unloading the diseased knee [64]. Knee OA, resulting in
biomechanical changes of the lower limb during level
walking, affects an increasing proportion of the population.
Compared to the normal group, patients with mild and
severe bilateral medial knee OA all had obviously increased
pelvic anterior tilt, swing-pelvis list, decreased standing
knee abduction, as well as decreased standing hip flexor
and knee extensor moments. The severe group also
demonstrated increased hip abduction, knee extension and
ankle plantarflexion. For the mild group, listing and ante-
rior tilting of the pelvis were responsible for successfully
reducing the extensor moment and maintaining a normal
abductor moment at the diseased knee. At the expense of
a greater hip abductor moment and with extra compensa-
tory changes at other joints, the severe group successfully
diminished the knee extensor moment but failed to
decrease the abductor moment. These results suggest that,
in addition to training of the knee muscles, training of the
hip muscles and pelvic control are essential for rehabili-
tating patients with knee OA, especially for patients with
more severe OA [64].
Gait analysis was also useful for investigating the effects
of treatment on gait patterns in patients with knee OA.
While TKR has been the main choice of treatment for
advanced knee OA, acupuncture has been a popular alter-
native in managing patients with mild to moderate knee
OA. Acupuncture has been shown to be effective in pain
relief and anesthesia [27,74e78], and has been suggested in
traditional Chinese medicine for treating various types of
functional disabilities, including knee OA. After acupunc-
ture stimulation, patients with bilateral medial compart-
ment knee OA reported significantly reduced pain and
walked with higher speed and greater step length, as well
as better body weight transfer through increased dynamic
joint ranges of motion and increased joint moments. The
differences between the two groups after treatment
suggest that the significantly improved gait performance in
the experimental group may be associated with the pain
relief after treatment, but the relatively small decrease in
pain in the sham group, even without subjective factors
involved, was not enough to induce significant improve-
ments in gait patterns. Gait analysis combined with the
visual analog scales can be useful for evaluating the true
effect of acupuncture treatment for patients with neuro-
musculoskeletal diseases and movement disorders [66]. The
study not only demonstrated the short-term effects of
acupuncture treatment on knee OA, but also justified the
need for study of its long-term effects.
Another example is the study of patients with anterior
cruciate ligament deficiency (ACLD) during obstacle-
crossing. The ACL has both structural and proprioceptive
functions so ACLD is known to lead to instability, a decrease
of the muscular strength, and impaired somatosensory
feedback of the knee [79]. Obstacle-crossing presents an
ideal motor task in which both the structural and proprio-
ceptive functions of the ACL can be evaluated because
a safe and successful obstacle-crossing requires stability of
the body provided mainly by the stance limb and sufficient
foot clearance of the swing limb. The former depends on
the stability of the joints while the latter emphasizes the
sensory function of the joints. These demands may not be
met in ACLD patients who have impairments in both
structural stability and sensory feedback of the affected
joint, or patients who have restored structural stability but
have residual impaired sensory feedback of the affected
joint after anterior cruciate ligament reconstruction
(ACLR). Therefore, detailed analysis and study of the ACLD
subjects during obstacle-crossing would be helpful for
establishing a more complete picture of the integration and
interaction of the structural and sensory functions of the
ACL during functional activity. In the study by Lu et al. [80],
patients with ACLD were found to show statistically the
same toe-obstacle clearance, crossing speeds, heel-
obstacle distances and toe-obstacle distances when
crossing obstacles with the unaffected limb leading
compared to healthy controls. However, they showed
significantly increased peak hip extensor and ankle plan-
tarflexor moments and decreased peak knee extensor
moments in the affected stance limb, with significant
increases in the anterior tilt of the pelvis and flexion at
both hips when the unaffected leading toe was above the
obstacle. These results suggest that patients with ACLD
adopted a strategy of decreasing the peak knee extensor
moments (quadriceps net effort) in order to avoid anterior
displacement of the tibia of the affected trailing stance
limb during obstacle-crossing. In order to prevent quadri-
ceps contraction, patients with ACLD may have to shift the
center of body mass forward and thus cause greater pelvic
anterior tilt and hip flexion, both in the swing and stance
limb, with normal leading toe-clearance for safe obstacle-
crossing [80].
These examples demonstrate the use of motion analysis
in evaluating pathology of the neuromusculoskeletal system
and assessing treatment. The analysis results are also
helpful for improving the management of relevant patient
populations.
Prevention of injury, design of prostheses
orthoses in rehabilitation
Since Dr. Vern Inman initially applied gait analysis to lower
limb prostheses research [8], it has been clear that study of
gait not only allows a better understanding of the neuro-
musculoskeletal compensations for underlying pathologies,
but also helps identify the mechanisms of abnormal gait.
Study of pathological and/or assisted gait enable the
evaluation of the efficacy of orthoses, such as functional
knee braces and lateral-wedged insoles, and the design and
development of fall-prevention strategies during obstacle-
crossing.
Use of functional knee braces has been suggested to
provide protection and to improve kinetic performance of
the knee in ACL-injured patients. However, the efficacy of
knee bracing in achieving these goals is still controversial.
Lu et al. [29] compared the 3D kinetics of the knee between
bracing conditions and between limbs in order to under-
stand the immediate effects of functional bracing on
walking performance in individuals with ACL injuries,
Biomechanics of human movement S21

10. including ACLD and ACLR subjects. They found that func-
tional knee bracing did not significantly affect the kinetics
of the unaffected knees for either group. For the ACLD
group, bracing significantly increased the peak abductor
moments in the affected knees and reduced the bilateral
kinetic asymmetry in the frontal plane. With functional
knee braces, significantly greater peak moments and
impulses of the abductors and extensors, and reduced
bilateral kinetic asymmetry in the sagittal and frontal
planes, were found in the ACLR group. For ACLR patients,
functional bracing can be recommended to help achieve
better bilateral kinetic symmetry during gait. For ACLD
patients, in addition to bracing, supplementary emphasis
on rehabilitative exercise for better kinetic knee perfor-
mance in the sagittal plane is needed [29].
Hemiparetic subjects after a cerebral vascular accident
or stroke may show reduced functional walking ability
owing to impaired ankle and knee control. In order to
increase weight bearing over the paretic side during stance,
and to correct abnormal gait patterns during walking, an
ankle-foot orthosis on the paretic limb is frequently
prescribed for these patients. Motion analysis was used to
assess the immediate effects of a 5
lateral-wedged insole,
applied to either the nonparetic or the paretic side, on the
weight-bearing symmetry and the moment changes of
lower-limb joints in stroke patients with hemiparesis [55].
The use of a lateral-wedged insole over the nonparetic side
was shown to improve the stance symmetry and tended to
reduce the paretic knee abductor loads. Applying the
wedged-insole on the paretic side during ambulation would
significantly decrease the abductor moments at the ipsi-
lateral hip and knee when compared to the contralateral
side (nonparetic side) [55].
Falls as a result of unsuccessfully negotiating obstacles
often lead to physical injuries which may result in great
costs including medical and social expenses. Knowledge of
the mechanics of the locomotor system and control strat-
egies adopted during this activity is helpful for under-
standing and identifying the risk factors for tripping which
are important for preventing falls, for the design of fall-
prevention devices and for planning programs aimed at
preventing trip-related falls [23,57,62,63,65,69,71,81e87].
Because the elderly [82,83] and older patients with knee OA
[62,65], highly functioning patients subsequent to stroke
[57] and patients with type II DM [71] are shown to be highly
prone to falling, the author studied the biomechanical
differences between the elderly or these patient groups
and healthy young subjects in this functional activity. Apart
from using traditional kinematic and kinetic analyses,
a novel approach, namely quantification of the interjoint
coordination using the continuous relative phase (CRP)
method, was used to study obstacle-crossing. Interjoint
coordination provides information on how the neuro-
musculoskeletal system organizes the redundant degrees of
freedom (DOF) of the joints in order to achieve a smooth,
efficient and accurate functional movement [88]. There-
fore, analyses of the patterns and variability of the inter-
joint coordination were performed to gain more insight into
the control of the locomotor system in normal adults [84],
and to identify the control deficits in the elderly [87] and
patients with knee OA [69] during obstacle negotiation.
Sports medicine
Sports biomechanics is a very active area within the field of
biomechanical research. The specific goals of sports
biomechanics research include performance enhancement,
injury prevention and safety for many elite, leisure and
rehabilitation sports. Motion analysis plays a key role in
professional sports training, aiming to optimize and
improve athletic performance. Examples include deter-
mining joint loadings in the lower extremities during ellip-
tical exercises [89] and their changes with different pedal
rates [90], step lengths [91] and step heights [92] and study
of the joint kinematics of the lower limbs and the COP
movements in wrestlers during tackle defense [93].
Elliptical exercise (EE) has been developed as a low-
impact aerobic exercise modality and has been shown to be
beneficial for developing and maintaining cardiorespiratory
fitness. Over the last decade it has increased in popularity
in fitness training and clinical applications. During EE, the
feet are constrained by pedals to follow an elliptical
trajectory which could lead to the possibility of producing
disadvantageous joint loads. In addition, the forces trans-
mitted in the lower limbs were found to be closely related
to potential musculoskeletal overuse injuries [89]. There-
fore, complete knowledge of the loading in the lower limbs
during EE is helpful for improving the design of elliptical
trainers (ET) and is essential for ensuring an efficient and
safe exercise environment, especially for patients.
However, little is known regarding the loadings applied to
the lower limb during EE. The author used a detailed 3D
dynamic analysis of the lower extremities to determine the
differences in lower-limb kinematics and kinetics between
EE and level walking. The results showed that EE had
smaller loading rates around heelstrike when compared to
level walking [89]. Reduced vertical pedal reaction force
(PRF) and loading rates during EE were achieved by greater
compensatory hip flexor and knee extensor moments [89].
Therefore, users’ joint function and muscle strength,
especially at the knee, must be considered in order to avoid
injuries when using ET for athletic and rehabilitative
training [89]. The effects of pedal rates, step height and
step length on the biomechanics of lower limbs during EE
were also studied [90e92]. With increasing pedal rates, the
medial, anterior and posterior PRF, as well as the medial
and vertical loading rates, all increased during EE [90]. As
step length increases, harmful joint loadings, especially at
the hip joint, could increase during EE [91]. When step
height increased, a more flexed posture achieved by
greater peak hip and knee flexion and hip abduction during
swing phase were used to compensate for the change in
pedal trajectory and to keep the body stable [92].
Increased hip extensor and decreased knee extensor
moments in late swing then occurred in the more flexed
posture in conjunction with reduced posterior shear forces
that could shift the line of action of the PRF more anterior
to the hip joint center and less posterior to the knee joint
center. Therefore, the harmful joint loadings, in particular
at the knee joints, and the corresponding risks of injuries
may be reduced during EE with increasing step heights [92].
Wrestling is one of the oldest and most popular
competitive sports in the world. However, knowledge of the
S22 T.-W. Lu, C.-F. Chang

11. biomechanics of wrestling is limited and the biomechanical
risk factors of injuries are still unclear. The author used 3D
motion analysis to investigate the joint kinematics of the
lower limbs and the COP movements in Greco-Roman style
(GR) and free style (FS) wrestlers during defense tackle
from three different directions [93]. The results showed
that the wrestlers who majored in GR had the tendency to
resist tackle attacks longer than the FS group. The FS
wrestlers tended to have greater anterior-posterior (A/P)
motion of the COP with significant increased knee flexion
when compared to the GR group. This flexed knee strategy
may be related to the training the FS wrestlers received and
the rules of the sport. Significantly increased transverse-
and frontal-plane joint angles at the knee and ankle may be
the risk factors related to the knee and ankle injuries
commonly found in wrestlers. Therefore, it was suggested
that strengthening of the lower-limb muscles may be
helpful for reducing these injuries during wrestling
competitions [93].
These examples show that motion analysis is an efficient
technique for identifying beneficial and damaging factors in
performing sports and exercises.
Conclusions
Universal gravitation affects all life forms on earth. Our body
is constantly subject to forces from within and surrounding
the body. Through the study of the interaction of the forces
and their effects on the body, the form, function and motion
of our biological body can be studied and the resulting
knowledge can be applied to promoting quality of life. Using
stereophotogrammetry-based human motion analysis tech-
niques combined with measured GRFs and muscle activities,
deviations from normal kinematic, kinetic or EMG patterns
can be identified and then used to evaluate neuro-
musculoskeletal conditions, to help with subsequent treat-
ment planning, and to assess the efficacy of treatments in
various patient groups. It can also be used to improve athletic
performance and to help identify posture- or movement-
related problems in people with injuries or diseases. Further
establishment of the biomechanics of human movement and
its clinical applications will benefit from the integration of
existing engineering techniques and the continuing devel-
opment of new technology.
Acknowledgments
The authors gratefully acknowledge Sheng-Chang Chen,
Wei-Chun Hsu, Hao-Ling Chen, Tsung-Yuan Tsai, Hui-Lien
Chien, Yen-Hung Liu, Shih-Wun Hong, Hsiao-Ching Yen, Mei-
Ying Kuo, Horng-Chaung Hsu, Ting-Ming Wang, Ming-Wei
Liu, I-Pin Wei, Jaung-Geng Lin, Chien-Hsun Chen, Kwan-
Hwa Lin, and Tsong-Rong Jang for their help in collecting
materials reported on in this paper.
References
[1] Clinical Gait Analysis, University of Vienna, Austria. History of
the study of locomotion. http://www.univie.ac.at/cga/
history/.
[2] Nigg BM, Herzog W. Biomechanics of the musculo-skeletal
system. 3rd ed. Hoboken NJ: John Wiley Sons; 2007.
[3] Watkins J. Structure and function of the musculoskeletal
system. Champaign: Human Kinetics; 1999.
[4] Bergmann G, Deuretzbacher G, Heller M, Graichen F,
Rohlmann A, Strauss J, et al. Hip contact forces and gait
patterns from routine activities. J Biomech 2001;34:859e71.
[5] Heller MO, Bergmann G, Deuretzbacher G, Durselen L, Pohl M,
Claes L, et al. Musculo-skeletal loading conditions at the hip
during walking and stair climbing. J Biomech 2001;34:883e93.
[6] Lu TW, Taylor SJ, O’Connor JJ, Walker PS. Influence of muscle
activity on the forces in the femur: an in vivo study. J Biomech
1997;30:1101e6.
[7] Stansfield BW, Nicol AC, Paul JP, Kelly IG, Graichen F,
Bergmann G. Direct comparison of calculated hip joint contact
forces with those measured using instrumented implants. An
evaluation of a three-dimensional mathematical model of the
lower limb. J Biomech 2003;36:929e36.
[8] Allard P, Stokes IAF, Blanchi JP. Three-dimensional analysis of
human movement. Champaign, IL: Human Kinetics Publishers;
1995.
[9] Lu TW. Geometric and mechanical modelling of the human
locomotor system. Oxford: University of Oxford; 1997.
[10] Cappozzo A, Della Croce U, Leardini A, Chiari L. Human
movement analysis using stereophotogrammetry. Part 1:
theoretical background. Gait Posture 2005;21:186e96.
[11] Andriacchi TP, Alexander EJ. Studies of human locomotion:
past, present and future. J Biomech 2000;33:1217e24.
[12] Center for Photogrammetric Training, Ferris State University.
History of photogrammetry. Michigan: Ferris State University;
2008.
[13] Chiari L, Della Croce U, Leardini A, Cappozzo A. Human
movement analysis using stereophotogrammetry. Part 2:
instrumental errors. Gait Posture 2005;21:197e211.
[14] Sutherland DH. The evolution of clinical gait analysis part l:
kinesiological EMG. Gait Posture 2001;14:61e70.
[15] Perry J. Gait analysis: normal and pathological function.
Thorofare, N.J.: Slack; 1992.
[16] Sutherland DH, Olshen R, Cooper L, Woo SL. The development
of mature gait. J Bone Joint Surg Am 1980;62:336e53.
[17] Sutherland DH. The development of mature gait. Gait Posture
1997;6:163e70.
[18] Gage JR. Gait analysis for decision-making in cerebral palsy.
Bull Hosp Joint Dis Orthop Inst 1983;43:147e63.
[19] Gage JR. Gait analysis in cerebral palsy. London: Mac Keith
Press; 1991.
[20] Kay RM, Dennis S, Rethlefsen S, Reynolds RA, Skaggs DL,
Tolo VT, et al. The effect of preoperative gait analysis on
orthopaedic decision making. Clin Orthop Rel Res 2000;372:
217e22.
[21] Lu TW, O’Connor JJ. Lines of action and moment arms of the
major force-bearing structures crossing the human knee joint:
comparison between theory and experiment. J Anat 1996;189:
575e85.
[22] Lu TW, O’Connor JJ, Taylor SJ, Walker PS. Validation of
a lower limb model with in vivo femoral forces telemetered
from two subjects. J Biomech 1998;31:63e9.
[23] Chen HL, Lu TW. Comparisons of the joint moments between
leading and trailing limb in young adults when stepping over
obstacles. Gait Posture 2006;23:69e77.
[24] Kuo MY, Hsu HC, Chang LY, Li GJ, Lu TW. A method for the
measurement of the three-dimensional kinematics of the
ankle-foot complex with footwear during activities. J Chin
Med Sci 2002;3:43e52.
[25] Lin HC, Lu TW, Hsu HC. Three-dimensional analysis of kine-
matic and kinetic coordination of the lower limb joints during
stair ascent and descent. Biomed Eng Appl Basis Comm 2004;
16:101e8.
Biomechanics of human movement S23

12. [26] Lin HC, Lu TW, Hsu HC. Comparisons of joint kinetics in the
lower extremity between stair ascent and descent. J Mech
2005;21:41e50.
[27] Lin JG, Chen CT, Lu TW, Lin YS, Chen HL, Chen YS. Quanti-
tative evaluation of the motion of frozen shoulders treated
with acupuncture by puncturing from Tiaokou (St. 38) towards
Chengshan (U.B. 57). Biomed Eng Appl Basis Comm 2005;17:
31e7.
[28] Lu TW. On the estimation of hip joint centre position in clin-
ical gait analysis. Biomed Eng Appl Basis Comm 2000;12:
89e95.
[29] Lu TW, Lin HC, Hsu HC. Influence of functional bracing on the
kinetics of anterior cruciate ligament-injured knees during
level walking. Clin Biomech 2006;21:517e24.
[30] Lu TW, Lu CH. Forces transmitted in the knee joint during stair
ascent and descent. J Mech 2006;22:289e97.
[31] Luo HJ, Jeng SF, Lu TW, Lin KH. Relationship between step-
ping movements and age of walking attainment in full-term
infants without known impairment or pathology. FJPT 2004;
29:67e78.
[32] Shih KS, Lin SC, Liu YH, Chang TH, Hou SM, Lu TW. Kinematic
study of an innovative dynamic bridging wrist external fixator
with arthrodiatasis. J Mech 2010;26:187e94.
[33] Shih KS, Lu TW, Fu YC, Hou SM, Sun JS, Cheng CY. Biomechanical
analysis of nonconstrained and semiconstrained total elbow
replacements: a preliminary report. J Mech 2008;24:103e10.
[34] Mills PM, Morrison S, Lloyd DG, Barrett RS. Repeatability of 3D
gait kinematics obtained from an electromagnetic tracking
system during treadmill locomotion. J Biomech 2007;40:
1504e11.
[35] Yang JL, Lu TW, Chou FC, Chang CW, Lin JJ. Secondary
motions of the shoulder during arm elevation in patients with
shoulder tightness. J Electromyogr Kinesiol 2009;19:1035e42.
[36] Lafortune MA, Cavanagh PR, Sommer 3rd HJ, Kalenak A.
Three-dimensional kinematics of the human knee during
walking. J Biomech 1992;25:347e57.
[37] Leardini A, Chiari L, Croce UD, Cappozzo A. Human movement
analysis using stereophotogrammetry: part 3. Soft tissue
artifact assessment and compensation. Gait Posture 2005;21:
212e25.
[38] Lu TW, O’Connor JJ. Bone position estimation from skin
marker co-ordinates using global optimisation with joint
constraints. J Biomech 1999;32:129e34.
[39] Cappozzo A, Catani F, Leardini A, Benedetti M, Croce U.
Position and orientation in space of bones during movement:
experimental artefacts. Clin Biomech (Bristol, Avon) 1996;11:
90e100.
[40] Reinschmidt C, van den Bogert AJ, Nigg BM, Lundberg A,
Murphy N. Effect of skin movement on the analysis of skeletal
knee joint motion during running. J Biomech 1997;30:729e32.
[41] Manal K, McClay I, Stanhope S, Richards J, Galinat B.
Comparison of surface mounted markers and attachment
methods in estimating tibial rotations during walking: an
in vivo study. Gait Posture 2000;11:38e45.
[42] Sangeux M, Marin F, Charleux F, Durselen L, Ho Ba Tho MC.
Quantification of the 3D relative movement of external
marker sets vs. bones based on magnetic resonance imaging.
Clin Biomech 2006;21:984e91.
[43] Sati M, de Guise JA, Larouche S, Drouin G. Quantitative
assessment of skin-bone movement at the knee. Knee 1996;3:
121e38.
[44] Stagni R, Fantozzi S, Cappello A, Leardini A. Quantification of
soft tissue artefact in motion analysis by combining 3D fluo-
roscopy and stereophotogrammetry: a study on two subjects.
Clin Biomech 2005;20:320e9.
[45] Banks SA, Hodge WA. Accurate measurement of three-
dimensional knee replacement kinematics using single-plane
fluoroscopy. IEEE Trans Biomed Eng 1996;43:638e49.
[46] Kaptein BL, Valstar ER, Stoel BC, Rozing PM, Reiber JHC. A
new model-based RSA method validated using CAD models and
models from reversed engineering. J Biomech 2003;36:
873e82.
[47] Tashman S, Anderst W. In-vivo measurement of dynamic joint
motion using high speed biplane radiography and CT: appli-
cation to canine ACL deficiency. J Biomech Eng-Trans ASME
2003;125:238e45.
[48] Dennis DA, Mahfouz MR, Komistek RD, Hoff W. In vivo deter-
mination of normal and anterior cruciate ligament-deficient
knee kinematics. J Biomech 2005;38:241e53.
[49] Banks SA, Fregly BJ, Boniforti F, Reinschmidt C, Romagnoli S.
Comparing in vivo kinematics of unicondylar and bi-
unicondylar knee replacements. Knee Surg Sports Traumatol
Arthrosc 2005;13:551e6.
[50] Tsai TY, Lu TW, Chen CM, Kuo MY, Hsu HC. A volumetric model-
based 2D to 3D registration method for measuring kinematics
of natural knees with single-plane fluoroscopy. Med Phys 2010;
37:1273e84.
[51] Zuffi S, Leardini A, Catani F, Fantozzi S, Cappello A. A model-
based method for the reconstruction of total knee replace-
ment kinematics. IEEE Trans Med Imaging 1999;18:981e91.
[52] Lu TW, Tsai TY, Kuo MY, Hsu HC, Chen HL. In vivo three-
dimensional kinematics of the normal knee during active
extension under unloaded and loaded conditions using single-
plane fluoroscopy. Med Eng Phys 2008;30:1004e12.
[53] Mahfouz MR, Hoff WA, Komistek RD, Dennis DA. A robust
method for registration of three-dimensional knee implant
models to two-dimensional fluoroscopy images. IEEE Trans
Med Imaging 2003;22:1561e74.
[54] Tsai TY, Lu TW, Kuo MY, Hsu HC. Quantification of three-
dimensional movement of skin markers relative to the
underlying bones during functional activities. Biomed Eng
Appl Basis Comm 2009;21:223e32.
[55] Chen CH, Lin KH, Lu TW, Chai HM, Chen HL, Tang PF, et al.
Immediate effect of lateral-wedged insole on stance and
ambulation after stroke. Am J Phys Med Rehabil 2010;89:
48e55.
[56] Fatone S, Gard SA, Malas BS. Effect of ankle-foot orthosis
alignment and foot-plate length on the gait of adults with
poststroke hemiplegia. Arch Phys Med Rehabil 2009;90:810e8.
[57] Lu TW, Yen HC, Chen HL, Hsu WC, Chen SC, Hong SW, et al.
Symmetrical kinematic changes in highly functioning older
patients post stroke during obstacle-crossing. Gait Posture
2010;31:511e6.
[58] Neckel ND, Blonien N, Nichols D, Hidler J. Abnormal joint
torque patterns exhibited by chronic stroke subjects while
walking with a prescribed physiological gait pattern. J Neu-
roEng Rehabil 2008;5:19.
[59] Said CM, Galea M, Lythgo N. Obstacle crossing performance
does not differ between the first and subsequent attempts in
people with stroke. Gait Posture 2009;30:455e8.
[60] Wu CY, Chou SH, Chen CL, Kuo MY, Lu TW, Fu YC. Kinematic
analysis of a functional and sequential bimanual task in
patients with left hemiparesis: intra-limb and interlimb
coordination. Disabil Rehabil 2009;31:958e66.
[61] Wu CY, Chou SH, Kuo MY, Chen CL, Lu TW, Fu YC. Effects of
object size on intralimb and interlimb coordination during
a bimanual prehension task in patients with left cerebral
vascular accidents. Motor Control 2008;12:296e310.
[62] Chen HL, Lu TW, Wang TM, Huang SC. Biomechanical strate-
gies for successful obstacle crossing with the trailing limb in
older adults with medial compartment knee osteoarthritis.
J Biomech 2008;41:753e61.
[63] Hsu WC, Wang TM, Liu MW, Chang CF, Chen HL, Lu TW. Control
of body center of mass motion during level walking and
obstacle-crossing in older patients with knee osteoarthritis. J
Mech 2010;26:229e37.
S24 T.-W. Lu, C.-F. Chang

13. [64] Huang SC, Wei IP, Chien HL, Wang TM, Liu YH, Chen HL, et al.
Effects of severity of degeneration on gait patterns in patients
with medial knee osteoarthritis. Med Eng Phys 2008;30:
997e1003.
[65] Lu TW, Chen HL, Wang TM. Obstacle crossing in older adults
with medial compartment knee osteoarthritis. Gait Posture
2007;26:553e9.
[66] Lu TW, Wei IP, Liu YH, Wang TM, Hsu WC, Chang CF, et al.
Immediate effects of acupuncture on gait patterns in patient
with knee osteoarthritis. Chin Med J 2010;123:165e72.
[67] Wang TM, Hsu WC, Chang CF, Hu CC, Lu TW. Effects of knee
osteoarthritis on body’s center of mass motion in older adults
during level walking. Biomed Eng Appl Basis Comm 2010;22:
205e12.
[68] Wei IP, Hsu WC, Chien HL, Chang CF, Liu YH, Ho TJ, et al. Leg
and joint stiffness in patients with bilateral medial knee
osteoarthritis during level walking. J Mech 2009;25:279e87.
[69] Wang TM, Yen HC, Lu TW, Chen HL, Chang CF, Liu YH, et al.
Bilateral knee osteoarthritis does not affect inter-joint coor-
dination in older adults with gait deviations during obstacle-
crossing. J Biomech 2009;42:2349e56.
[70] Hsu WC, Lu TW, Liu MW. Lower limb joint position sense in
patients with type II diabetes mellitus. Biomed Eng Appl Basis
Comm 2009;21:271e8.
[71] Liu MW, Hsu WC, Lu TW, Chen HL, Liu HC. Patients with type II
diabetes mellitus display reduced toe-obstacle clearance with
altered gait patterns during obstacle-crossing. Gait Posture
2010;31:93e9.
[72] Lin KH, Lu TW, Hsu PP, Yu SM, Liao WS. Postural responses
during falling with rapid reach-and-grasp balance reaction in
patients with motor complete paraplegia. Spinal Cord 2008;
46:204e9.
[73] DeLuca PA, Davis 3rd RB, Ounpuu S, Rose S, Sirkin R. Alter-
ations in surgical decision making in patients with cerebral
palsy based on three-dimensional gait analysis. J Pediatr
Orthop 1997;17:608e14.
[74] Ezzo J, Berman B, Hadhazy VA, Jadad AR, Lao L, Singh BB. Is
acupuncture effective for the treatment of chronic pain? A
systematic review. Pain 2000;86:217e25.
[75] Fischer MV, Behr A, von Reumont J. Acupuncture e a thera-
peutic concept in the treatment of painful conditions and
functional disorders. Report on 971 cases. Acupunct Electro-
ther Res 1984;9:11e29.
[76] Lin JG. A concept in analgesic mechanisms of acupuncture.
Chin Med J 1996;109:185e8.
[77] O’Connor J, Bensky D. A summary of research concerning the
effects of acupuncture. Am J Chin Med 1975;3:377e94.
[78] Thomas M, Eriksson SV, Lundeberg T. A comparative study of
diazepam and acupuncture in patients with osteoarthritis
pain: a placebo controlled study. Am J Chin Med 1991;19:
95e100.
[79] Noyes FR, Matthews DS, Mooar PA, Grood ES. The symptomatic
anterior cruciate-deficient knee. Part II: the results of reha-
bilitation, activity modification, and counseling on functional
disability. J Bone Joint Surg-Am Vol 1983;65:163e74.
[80] Lu TW, Hong SW, Hsu HC. Adopted biomechanical strategies
for crossing obstacles of different heights in anterior cruciate
ligament deficient subjects when unaffected limb leading. 6th
World Congress of Biomechanics; 2010.
[81] Chen HL, Lu TW, Lin HC. Three-dimensional kinematic analysis
of stepping over obstacles in young subjects. Biomed Eng Appl
Basis Comm 2004;16:157e64.
[82] Huang SC, Lu TW, Chen HL, Wang TM, Chou LS. Age and height
effects on the center of mass and center of pressure inclina-
tion angles during obstacle-crossing. Med Eng Phys 2008;30:
968e75.
[83] Lu TW, Chen HL, Chen SC. Comparisons of the lower limb
kinematics between young and older adults when crossing
obstacles of different heights. Gait Posture 2006;23:471e9.
[84] Lu TW, Yen HC, Chen HL. Comparisons of the inter-joint coor-
dination between leading and trailing limbs when crossing
obstacles of different heights. Gait Posture 2008;27:309e15.
[85] Wang TM, Chen HL, Hsu WC, Liu MW, Chang CF, Lu TW.
Biomechanical role of the locomotor system in controlling
body center of mass motion in older adults during obstructed
gait. J Mech 2010;26:195e203.
[86] Wang TM, Chen HL, Lu TW. Effects of obstacle height on the
control of the body center of mass motion during obstructed
gait. J Chin Inst Eng 2007;30:471e9.
[87] Yen HC, Chen HL, Liu MW, Liu HC, Lu TW. Age effects on the
inter-joint coordination during obstacle-crossing. J Biomech
2009;42:2501e6.
[88] Bernstein N. The co-ordination and regulation of movements.
Oxford: Pergamon Press; 1967.
[89] Lu TW, Chien HL, Chen HL. Joint loading in the lower
extremities during elliptical exercise. Med Sci Sports Exerc
2007;39:1651e8.
[90] Chien HL, Tsai TY, Lu TW. The effects of pedal rates on pedal
reaction forces during elliptical exercise. Biomed Eng Appl
Basis Comm 2007;19:207e14.
[91] Lu TW, Huang CH, Chen YP, Chang CF, Chien HL. Effects of
step length on the biomechanics of lower limbs during ellip-
tical exercise. 27th International Society of Biomechanics in
Sports Conference; Ireland: August 17e21 2009.
[92] Chen YP, Chang CF, Chien HL, Chen YC, Lu TW. Step height
effects on lower limb biomechanics and body centre of mass
motion during elliptical exercise. 27th International Society of
Biomechanics in Sports Conference; Ireland: August 17e21
2009.
[93] Jang TR, Chang CF, Chen SC, Fu YC, Lu TW. Biomechanics and
potential injury mechanisms of wrestling. Biomed Eng Appl
Basis Comm 2009;21:215e22.
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